{"id":"https://openalex.org/W2126721611","doi":"https://doi.org/10.1109/ijcnn.2004.1380964","title":"Information criteria for reduced rank canonical correlation analysis","display_name":"Information criteria for reduced rank canonical correlation analysis","publication_year":2005,"publication_date":"2005-01-31","ids":{"openalex":"https://openalex.org/W2126721611","doi":"https://doi.org/10.1109/ijcnn.2004.1380964","mag":"2126721611"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2004.1380964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1380964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024426963","display_name":"M.A. Hasan","orcid":"https://orcid.org/0000-0003-4103-7945"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210115145","display_name":"University of Minnesota, Duluth","ror":"https://ror.org/01hy4qx27","country_code":"US","type":"education","lineage":["https://openalex.org/I4210115145"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M.A. Hasan","raw_affiliation_strings":["Department of Electrical & Computer Engineering, University of Minnesota, Duluth, USA","Dept. of Electr. & Comput. Eng., Univ. of Minnesota Duluth, MN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, University of Minnesota, Duluth, USA","institution_ids":["https://openalex.org/I4210115145"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Minnesota Duluth, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5024426963"],"corresponding_institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210115145"],"apc_list":null,"apc_paid":null,"fwci":0.6359,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.6992266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"2215","last_page":"2220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9811000227928162,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.9137111306190491},{"id":"https://openalex.org/keywords/canonical-analysis","display_name":"Canonical analysis","score":0.7195953130722046},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5836907625198364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5100648999214172},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49166494607925415},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4868852198123932},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4566870927810669},{"id":"https://openalex.org/keywords/canonical-form","display_name":"Canonical form","score":0.45639628171920776},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45057517290115356},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.44802507758140564},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.4431299567222595},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.41475534439086914},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.41087400913238525},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.32959145307540894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30777478218078613},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18109190464019775},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08060091733932495},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.0800626277923584}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.9137111306190491},{"id":"https://openalex.org/C75806538","wikidata":"https://www.wikidata.org/wiki/Q5033360","display_name":"Canonical analysis","level":2,"score":0.7195953130722046},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5836907625198364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5100648999214172},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49166494607925415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4868852198123932},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4566870927810669},{"id":"https://openalex.org/C204707403","wikidata":"https://www.wikidata.org/wiki/Q1152398","display_name":"Canonical form","level":2,"score":0.45639628171920776},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45057517290115356},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.44802507758140564},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.4431299567222595},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.41475534439086914},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.41087400913238525},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32959145307540894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30777478218078613},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18109190464019775},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08060091733932495},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0800626277923584},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2004.1380964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1380964","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1578953027","https://openalex.org/W1690722915","https://openalex.org/W1778065289","https://openalex.org/W1883480056","https://openalex.org/W1975077471","https://openalex.org/W2025341678","https://openalex.org/W2045218416","https://openalex.org/W2054315487","https://openalex.org/W2069264531","https://openalex.org/W2070645684","https://openalex.org/W2083440647","https://openalex.org/W2099194085","https://openalex.org/W2119501108","https://openalex.org/W2120041859","https://openalex.org/W2133515443","https://openalex.org/W2135591374","https://openalex.org/W2140984045","https://openalex.org/W2155381902","https://openalex.org/W4232604653","https://openalex.org/W4237723258","https://openalex.org/W4237951138"],"related_works":["https://openalex.org/W2121524531","https://openalex.org/W1565185441","https://openalex.org/W1968846550","https://openalex.org/W2047516836","https://openalex.org/W2079181692","https://openalex.org/W2525150876","https://openalex.org/W207577366","https://openalex.org/W2182589214","https://openalex.org/W2157498938","https://openalex.org/W2120081959"],"abstract_inverted_index":{"Canonical":[0],"correlation":[1],"analysis":[2],"is":[3,23,70,77,100],"an":[4],"essential":[5],"technique":[6],"in":[7,35],"the":[8,49,60,97],"field":[9],"of":[10,67,96],"multivariate":[11],"statistical":[12],"analysis.":[13],"In":[14],"this":[15,68,92],"paper,":[16],"a":[17],"framework":[18],"involving":[19],"unconstrained":[20],"optimization":[21],"criteria":[22,38],"proposed":[24,98],"for":[25,58,74],"extracting":[26],"multiple":[27],"canonical":[28,31,75],"variates":[29,76],"and":[30,34,85],"correlations":[32],"serially":[33],"parallel.":[36],"These":[37],"are":[39],"derived":[40],"from":[41],"optimizing":[42],"three":[43],"information":[44],"based":[45],"functions.":[46],"Based":[47],"on":[48],"gradient-ascent":[50],"or":[51],"descent":[52],"methods,":[53],"we":[54],"derive":[55],"many":[56],"algorithms":[57,99],"performing":[59],"true":[61],"CCA":[62],"recursively.":[63],"The":[64,80,94],"main":[65],"feature":[66],"approach":[69],"that":[71],"orthogonal":[72],"basis":[73],"automatically":[78],"obtained.":[79],"first":[81],"few":[82],"singular":[83],"values":[84],"vectors":[86],"can":[87],"also":[88],"be":[89],"obtained":[90],"using":[91],"framework.":[93],"performances":[95],"demonstated":[101],"through":[102],"simulations.":[103]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
